To develop a common internal standard for data classification, which groups should be involved?

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Multiple Choice

To develop a common internal standard for data classification, which groups should be involved?

Explanation:
Developing a common internal standard for data classification requires input from multiple parts of the organization. When stakeholders from across the organization collaborate, you bring in data owners who understand business context and sensitivity, data stewards who manage data quality and taxonomy, IT security for labeling and controls, compliance and legal for regulatory requirements, and risk management to assess impacts. This breadth ensures the standard covers all data types, fits actual workflows, and is practical to implement, which helps people adopt and consistently apply it. Relying on a single group—whether IT, external consultants, or any one department—risks missing important business perspectives, regulatory needs, or ongoing ownership, leading to a standard that’s incomplete or hard to enforce.

Developing a common internal standard for data classification requires input from multiple parts of the organization. When stakeholders from across the organization collaborate, you bring in data owners who understand business context and sensitivity, data stewards who manage data quality and taxonomy, IT security for labeling and controls, compliance and legal for regulatory requirements, and risk management to assess impacts. This breadth ensures the standard covers all data types, fits actual workflows, and is practical to implement, which helps people adopt and consistently apply it. Relying on a single group—whether IT, external consultants, or any one department—risks missing important business perspectives, regulatory needs, or ongoing ownership, leading to a standard that’s incomplete or hard to enforce.

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